ARTIFICIAL INTELLIGENCE SELF-LEARNING-BASED STATIC ELECTROCARDIOGRAPHY ANALYSIS METHOD AND APPARATUS
An artificial intelligence self-learning-based static electrocardiography analysis method and apparatus, said method comprising data preprocessing, heartbeat detection, heartbeat classification based on a depth learning method, heartbeat verification, heartbeat waveform feature detection, measuremen...
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| creator | LV, Youchao CAO, Jun ZHAO, Pengfei LIU, Chang ZANG, Kaifeng WANG, Erbin |
| description | An artificial intelligence self-learning-based static electrocardiography analysis method and apparatus, said method comprising data preprocessing, heartbeat detection, heartbeat classification based on a depth learning method, heartbeat verification, heartbeat waveform feature detection, measurement and analysis of electrocardiography events, and finally automatic output of reporting data, realizing an automated static electrocardiograph analysis method having a complete and rapid flow. The static electrocardiography analysis method can also record modification information of an automatic analysis result, collect modified data, and feed same back to the depth learning model to continue training, thereby continuously making improvements and improving the accuracy of the automatic analysis method.
L'invention concerne un procédé et un appareil d'analyse d'électrocardiographie statique basée sur un auto-apprentissage d'intelligence artificielle, ledit procédé comprenant un prétraitement de données, une détectio |
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L'invention concerne un procédé et un appareil d'analyse d'électrocardiographie statique basée sur un auto-apprentissage d'intelligence artificielle, ledit procédé comprenant un prétraitement de données, une détectio</description><language>chi ; eng ; fre</language><subject>DIAGNOSIS ; HUMAN NECESSITIES ; HYGIENE ; IDENTIFICATION ; MEDICAL OR VETERINARY SCIENCE ; SURGERY</subject><creationdate>2019</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20190531&DB=EPODOC&CC=WO&NR=2019100566A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76516</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20190531&DB=EPODOC&CC=WO&NR=2019100566A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>LV, Youchao</creatorcontrib><creatorcontrib>CAO, Jun</creatorcontrib><creatorcontrib>ZHAO, Pengfei</creatorcontrib><creatorcontrib>LIU, Chang</creatorcontrib><creatorcontrib>ZANG, Kaifeng</creatorcontrib><creatorcontrib>WANG, Erbin</creatorcontrib><title>ARTIFICIAL INTELLIGENCE SELF-LEARNING-BASED STATIC ELECTROCARDIOGRAPHY ANALYSIS METHOD AND APPARATUS</title><description>An artificial intelligence self-learning-based static electrocardiography analysis method and apparatus, said method comprising data preprocessing, heartbeat detection, heartbeat classification based on a depth learning method, heartbeat verification, heartbeat waveform feature detection, measurement and analysis of electrocardiography events, and finally automatic output of reporting data, realizing an automated static electrocardiograph analysis method having a complete and rapid flow. The static electrocardiography analysis method can also record modification information of an automatic analysis result, collect modified data, and feed same back to the depth learning model to continue training, thereby continuously making improvements and improving the accuracy of the automatic analysis method.
L'invention concerne un procédé et un appareil d'analyse d'électrocardiographie statique basée sur un auto-apprentissage d'intelligence artificielle, ledit procédé comprenant un prétraitement de données, une détectio</description><subject>DIAGNOSIS</subject><subject>HUMAN NECESSITIES</subject><subject>HYGIENE</subject><subject>IDENTIFICATION</subject><subject>MEDICAL OR VETERINARY SCIENCE</subject><subject>SURGERY</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2019</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNirEKwjAQQLM4iPoPAedCq1hwPNNre3AmITmRTqVonEQL9f-xgx_g8Hg8eEt1hyBUkyFgTVaQmRq0BnVErjNGCJZsk50gYqWjgJDRyGgkOAOhItcE8G2nwQJ3kaI-o7SumnvGewggl7hWi8fwnNLm55Xa1iimzdL47tM0Drf0Sp_-6nZ5cSzy_FCWUOz_u75CMTWx</recordid><startdate>20190531</startdate><enddate>20190531</enddate><creator>LV, Youchao</creator><creator>CAO, Jun</creator><creator>ZHAO, Pengfei</creator><creator>LIU, Chang</creator><creator>ZANG, Kaifeng</creator><creator>WANG, Erbin</creator><scope>EVB</scope></search><sort><creationdate>20190531</creationdate><title>ARTIFICIAL INTELLIGENCE SELF-LEARNING-BASED STATIC ELECTROCARDIOGRAPHY ANALYSIS METHOD AND APPARATUS</title><author>LV, Youchao ; CAO, Jun ; ZHAO, Pengfei ; LIU, Chang ; ZANG, Kaifeng ; WANG, Erbin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_WO2019100566A13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng ; fre</language><creationdate>2019</creationdate><topic>DIAGNOSIS</topic><topic>HUMAN NECESSITIES</topic><topic>HYGIENE</topic><topic>IDENTIFICATION</topic><topic>MEDICAL OR VETERINARY SCIENCE</topic><topic>SURGERY</topic><toplevel>online_resources</toplevel><creatorcontrib>LV, Youchao</creatorcontrib><creatorcontrib>CAO, Jun</creatorcontrib><creatorcontrib>ZHAO, Pengfei</creatorcontrib><creatorcontrib>LIU, Chang</creatorcontrib><creatorcontrib>ZANG, Kaifeng</creatorcontrib><creatorcontrib>WANG, Erbin</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>LV, Youchao</au><au>CAO, Jun</au><au>ZHAO, Pengfei</au><au>LIU, Chang</au><au>ZANG, Kaifeng</au><au>WANG, Erbin</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>ARTIFICIAL INTELLIGENCE SELF-LEARNING-BASED STATIC ELECTROCARDIOGRAPHY ANALYSIS METHOD AND APPARATUS</title><date>2019-05-31</date><risdate>2019</risdate><abstract>An artificial intelligence self-learning-based static electrocardiography analysis method and apparatus, said method comprising data preprocessing, heartbeat detection, heartbeat classification based on a depth learning method, heartbeat verification, heartbeat waveform feature detection, measurement and analysis of electrocardiography events, and finally automatic output of reporting data, realizing an automated static electrocardiograph analysis method having a complete and rapid flow. The static electrocardiography analysis method can also record modification information of an automatic analysis result, collect modified data, and feed same back to the depth learning model to continue training, thereby continuously making improvements and improving the accuracy of the automatic analysis method.
L'invention concerne un procédé et un appareil d'analyse d'électrocardiographie statique basée sur un auto-apprentissage d'intelligence artificielle, ledit procédé comprenant un prétraitement de données, une détectio</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | DIAGNOSIS HUMAN NECESSITIES HYGIENE IDENTIFICATION MEDICAL OR VETERINARY SCIENCE SURGERY |
| title | ARTIFICIAL INTELLIGENCE SELF-LEARNING-BASED STATIC ELECTROCARDIOGRAPHY ANALYSIS METHOD AND APPARATUS |
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